Important: The QnA Maker service will retire on the 31st of March, 2025. A newer version of the question and answering capability is now available as part of Azure Cognitive Service for Language. For question-and-answer capabilities within the Cognitive Services, see question answering. Starting 1st October, 2022 you won't be able to create new QnA Maker resources. For information on migrating existing QnA Maker knowledge bases to question answering, consult the migration guide. For an updated version of this sample that uses question answering, see the CustomQABotAllFeatures sample.
Bot Framework v4 QnA Maker bot sample. This sample shows how to integrate Multiturn and Active learning in a QnA Maker bot with Node.js. Click here to know more about using follow-up prompts to create multiturn conversation. To know more about how to enable and use active learning, click here.
This bot has been created using Bot Framework, it shows how to create a bot that uses the QnA Maker Cognitive AI service.
The QnA Maker Service enables you to build, train and publish a simple question and answer bot based on FAQ URLs, structured documents or editorial content in minutes. In this sample, we demonstrate how to use the QnA Maker service to answer questions based on a FAQ text file used as input.
The QnA Maker Service enables you to build, train and publish a simple question and answer bot based on FAQ URLs, structured documents or editorial content in minutes. In this sample, we demonstrate
- how to use the Active Learning to generate suggestions for knowledge base.
- how to use the Multiturn experience for the knowledge base .
- Follow instructions here to create a QnA Maker service.
- Follow instructions here to create multiturn experience.
- Follow instructions here to import and publish your newly created QnA Maker service.
- Update .env with your kbid (KnowledgeBase Id), endpointKey and endpointHost. You may also change the default answer by updating
DefaultAnswer
(optional) field. QnA knowledge base setup and application configuration steps can be found here. - (Optional) Follow instructions here to set up the QnA Maker CLI to deploy the model.
QnA knowledge base setup and application configuration steps can be found here.
- Create a Knowledge Base in QnAMaker Portal.
- Import "smartLightFAQ.tsv" file, in QnAMaker Portal.
- Save and Train the model.
- Create Bot from Publish page.
- Test bot with Web Chat.
- Capture values of settings like"QnAAuthKey" from
- "Configuration" page of created bot, in Azure Portal.
- Updated appsettings.json with values as needed.
- Use value of "QnAAuthKey" for setting "QnAEndpointKey".
- Capture KnowledgeBase Id, HostName and EndpointKey current published app
- Once your QnA Maker service is up and you have published the sample KB, try the following queries to trigger the Train API on the bot.
- Sample query: "light"
- You can observe that, Multiple answers are returned with high score.
- Once your QnA Maker service is up and you have published the sample KB, try the following queries to trigger the Train API on the bot.
- Sample query: "won't turn on"
- You can notice a prompt, included as part of answer to query.
This bot uses QnA Maker Service, an AI based cognitive service, to implement simple Question and Answer conversational patterns.
-
Node.js version 10.14 or higher
# determine node version node --version
-
Clone the repository
git clone https://github.com/microsoft/botbuilder-samples.git
-
In a terminal, navigate to
samples/javascript_nodejs/49.qnamaker-all-features
cd samples/javascript_nodejs/49.qnamaker-all-features
-
Install modules
npm install
-
Setup QnAMaker
The prerequisite outlined above contain the steps necessary to provision a QnA Knowledge Base on www.qnamaker.ai. Refer to Use QnA Maker to answer questions for directions to setup and configure QnAMaker.
-
Run the sample
npm start
- Goto
dialog/rootDialog.js
- Add reference
const { TurnContext } = require('botbuilder-core');
- Update
run
function asasync run(context, accessor) { const dialogSet = new DialogSet(accessor); dialogSet.add(this); const dialogContext = await dialogSet.createContext(context); if (context.activity.channelId === "msteams") { context.activity.text = TurnContext.removeRecipientMention(context.request); } const results = await dialogContext.continueDialog(); if (results.status === DialogTurnStatus.empty) { await dialogContext.beginDialog(this.id); } }
Bot Framework Emulator is a desktop application that allows bot developers to test and debug their bots on localhost or running remotely through a tunnel.
- Install the latest Bot Framework Emulator from here
- Launch Bot Framework Emulator
- File -> Open Bot
- Enter a Bot URL of
http://localhost:3978/api/messages
QnA Maker enables you to power a question and answer service from your semi-structured content.
One of the basic requirements in writing your own bot is to seed it with questions and answers. In many cases, the questions and answers already exist in content like FAQ URLs/documents, product manuals, etc. With QnA Maker, users can query your application in a natural, conversational manner. QnA Maker uses machine learning to extract relevant question-answer pairs from your content. It also uses powerful matching and ranking algorithms to provide the best possible match between the user query and the questions.
To learn more about deploying a bot to Azure, see Deploy your bot to Azure for a complete list of deployment instructions.